Identifying essential genes in a given organism is important for research on their fundamental roles in organism survival. Furthermore, if possible, uncovering the links between core functions or ...pathways with these essential genes will further help us obtain deep insight into the key roles of these genes. In this study, we investigated the essential and non-essential genes reported in a previous study and extracted gene ontology (GO) terms and biological pathways that are important for the determination of essential genes. Through the enrichment theory of GO and KEGG pathways, we encoded each essential/non-essential gene into a vector in which each component represented the relationship between the gene and one GO term or KEGG pathway. To analyze these relationships, the maximum relevance minimum redundancy (mRMR) was adopted. Then, the incremental feature selection (IFS) and support vector machine (SVM) were employed to extract important GO terms and KEGG pathways. A prediction model was built simultaneously using the extracted GO terms and KEGG pathways, which yielded nearly perfect performance, with a Matthews correlation coefficient of 0.951, for distinguishing essential and non-essential genes. To fully investigate the key factors influencing the fundamental roles of essential genes, the 21 most important GO terms and three KEGG pathways were analyzed in detail. In addition, several genes was provided in this study, which were predicted to be essential genes by our prediction model. We suggest that this study provides more functional and pathway information on the essential genes and provides a new way to investigate related problems.
Benzofuran compounds are a class of compounds that are ubiquitous in nature. Numerous studies have shown that most benzofuran compounds have strong biological activities such as anti-tumor, ...antibacterial, anti-oxidative, and anti-viral activities. Owing to these biological activities and potential applications in many aspects, benzofuran compounds have attracted more and more attention of chemical and pharmaceutical researchers worldwide, making these substances potential natural drug lead compounds. For example, the recently discovered novel macrocyclic benzofuran compound has anti-hepatitis C virus activity and is expected to be an effective therapeutic drug for hepatitis C disease; novel scaffold compounds of benzothiophene and benzofuran have been developed and utilized as anticancer agents. Novel methods for constructing benzofuran rings have been discovered in recent years. A complex benzofuran derivative is constructed by a unique free radical cyclization cascade, which is an excellent method for the synthesis of a series of difficult-to-prepare polycyclic benzofuran compounds. Another benzofuran ring constructed by proton quantum tunneling has not only fewer side reactions, but also high yield, which is conducive to the construction of complex benzofuran ring systems. This review summarizes the recent studies on the various aspects of benzofuran derivatives including their important natural product sources, biological activities and drug prospects, and chemical synthesis, as well as the relationship between the bioactivities and structures.
Benzofuran compounds are a class of compounds that are ubiquitous in nature.
Colorectal cancer is the third most common cancer in males and second in females. This disease can be caused by genetic and acquired/environmental factors. Microsatellite instability (MSI) is one of ...the major mechanisms in colorectal cancer. This mechanism is a specific condition of genetic hyper mutability that results from incompetent DNA mismatch repair. MSI has been applied to classify different colorectal cancer subtypes. However, the effects of MSI status on gene expression are largely unknown. In our study, we integrated the gene expression profile and MSI status of all CRC samples from the TCGA database, and then categorized the CRC samples into three subgroups, namely, MSI‐stable, MSI‐low, and MSI‐high, according to the MSI status. We applied a novel computational method based on machine learning and screened the genes specifically expressed for the different colorectal cancer subtypes. The results showed the distinct mechanisms of the different colorectal cancer subtypes with MSI status and provided the genes that may be the optimal standards to further classify the various molecular subtypes of colorectal cancer with distinct MSI status.
What's new?
Microsatellite instability (MSI), a key genetic mechanism implicated in colorectal cancer (CRC), is linked to drug reactivity and sensitivity in CRC patients and is useful for CRC subtype classification. Yet, little is known about the identity of MSI‐associated genes or their role in CRC. Here, combined analysis of datasets on gene‐expression profile and MSI status enabled the investigation of a number of differentially expressed genes from CRC samples. Genes optimal for the classification of CRC subtypes with different MSI statuses were identified. The gene panel could facilitate the discovery of biomarkers specific for CRCs with known MSI status.
Metabolic diseases are serious threats to public health and related to gut microbiota. Probiotics, prebiotics, synbiotics, and postbiotics (PPSP) are powerful regulators of gut microbiota, thus ...possessing prospects for preventing metabolic diseases. Therefore, the effects and mechanisms of PPSP on metabolic diseases targeting gut microbiota are worth discussing and clarifying. Generally, PPSP benefit metabolic diseases management, especially obesity and type 2 diabetes mellitus. The underlying gut microbial-related mechanisms are mainly the modulation of gut microbiota composition, regulation of gut microbial metabolites, and improvement of intestinal barrier function. Moreover, clinical trials showed the benefits of PPSP on patients with metabolic diseases, while the clinical strategies for gestational diabetes mellitus, optimal formula of synbiotics and health benefits of postbiotics need further study. This review fully summarizes the relationship between probiotics, prebiotics, synbiotics, postbiotics, and metabolic diseases, presents promising results and the one in dispute, and especially attention is paid to illustrates potential mechanisms and clinical effects, which could contribute to the next research and development of PPSP.
Abstract
Three kinds of nano-concrete, i.e., 2.0% nano-SiO
2
doped, 2.0% nano-CaCO
3
doped and 1.0% nano-SiO
2
-1.0% nano-CaCO
3
co-doped concretes (NS, NC, NSC) were prepared for a study on static ...property and dynamic property under different strain rates (50–130 s
−1
) using HYY series hydraulic servo test system and Φ100 mm split Hopkinson pressure bar test system, and a comparison with plain concrete (PC) as well. The results have shown that under static load, as compared with PC, NC has both strength and elastic modulus increased obviously, while NS has strength decreased and elastic modulus increased, and under dynamic load, there is an obvious strain rate effect for the dynamic compressive strength, impact toughness, energy dissipation and impact failure mode of concrete. Under the same strain rate, the dynamic compressive strength, peak strain, impact toughness and energy dissipation of NC are significantly increased, while its dynamic elastic modulus is decreased. Compared with PC, NS has dynamic compressive strength, peak strain, impact toughness and energy dissipation decreased, and dynamic elastic modulus increased, NC has static and dynamic mechanical properties improved, NS has static and dynamic mechanical properties weakened, and NSC is between PC and NC in static and dynamic mechanical properties, but generally improved. Doped with nano-CaCO
3
, NC has compactness improved, weak areas reduced, and pore size distribution optimized, while doped with nano-SiO
2
, NS has obvious internal weak areas, with pore structure degraded.
Under investigation in this paper is a (3+1)-dimensional nonlinear evolution equation, which was proposed and analyzed to study features and properties of nonlinear dynamics in higher dimensions. ...Using the Hirota bilinear method, we construct a bilinear Bäcklund transformation, which consists of four equations and involves six free parameters. With test function method and symbolic computation, three sets of lump–kink solutions and new types of interaction solutions are derived, and figures are presented to reveal the interaction behaviors. Setting constraints to the new interaction solution via the test function expressed by “polynomial-cos-cosh,” we simulate the periodic interaction phenomenon. Pfaffian solutions to the (3+1)-dimensional nonlinear evolution equation are obtained based on a set of linear partial differential conditions. According to our results, the diversity of solutions to the (3+1)-dimensional nonlinear evolution equation is revealed.
Nucleotide-binding, leucine-rich repeat receptors (NLRs) are major immune receptors in plants and animals. Upon activation, the Arabidopsis NLR protein ZAR1 forms a pentameric resistosome in vitro ...and triggers immune responses and cell death in plants. In this study, we employed single-molecule imaging to show that the activated ZAR1 protein can form pentameric complexes in the plasma membrane. The ZAR1 resistosome displayed ion channel activity in Xenopus oocytes in a manner dependent on a conserved acidic residue Glu11 situated in the channel pore. Pre-assembled ZAR1 resistosome was readily incorporated into planar lipid-bilayers and displayed calcium-permeable cation-selective channel activity. Furthermore, we show that activation of ZAR1 in the plant cell led to Glu11-dependent Ca2+ influx, perturbation of subcellular structures, production of reactive oxygen species, and cell death. The results thus support that the ZAR1 resistosome acts as a calcium-permeable cation channel to trigger immunity and cell death.
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•Resistosome formed by the immune receptor ZAR1 is a cation-selective channel•The ZAR1 channel is permeable to calcium•The activated ZAR1 forms a pentamer in the plasma membrane•The channel activity triggers immune signaling and cell death in plants
ZAR1 resistosome is a calcium-permeable channel that triggers immune signaling and cell death in plants.
Manganese is one of the most abundant elements on Earth. The oxidation of manganese has long been theorized
-yet has not been demonstrated
-to fuel the growth of chemolithoautotrophic microorganisms. ...Here we refine an enrichment culture that exhibits exponential growth dependent on Mn(II) oxidation to a co-culture of two microbial species. Oxidation required viable bacteria at permissive temperatures, which resulted in the generation of small nodules of manganese oxide with which the cells associated. The majority member of the culture-which we designate 'Candidatus Manganitrophus noduliformans'-is affiliated to the phylum Nitrospirae (also known as Nitrospirota), but is distantly related to known species of Nitrospira and Leptospirillum. We isolated the minority member, a betaproteobacterium that does not oxidize Mn(II) alone, and designate it Ramlibacter lithotrophicus. Stable-isotope probing revealed
CO
fixation into cellular biomass that was dependent upon Mn(II) oxidation. Transcriptomic analysis revealed candidate pathways for coupling extracellular manganese oxidation to aerobic energy conservation and autotrophic CO
fixation. These findings expand the known diversity of inorganic metabolisms that support life, and complete a biogeochemical energy cycle for manganese
that may interface with other major global elemental cycles.
Synthetic lethality is the synthesis of mutations leading to cell death. Tumor‐specific synthetic lethality has been targeted in research to improve cancer therapy. With the advances of techniques in ...molecular biology, such as RNAi and CRISPR/Cas9 gene editing, efforts have been made to systematically identify synthetic lethal interactions, especially for frequently mutated genes in cancers. However, elucidating the mechanism of synthetic lethality remains a challenge because of the complexity of its influencing conditions. In this study, we proposed a new computational method to identify critical functional features that can accurately predict synthetic lethal interactions. This method incorporates several machine learning algorithms and encodes protein‐coding genes by an enrichment system derived from gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways to represent their functional features. We built a random forest‐based prediction engine by using 2120 selected features and obtained a Matthews correlation coefficient of 0.532. We examined the top 15 features and found that most of them have potential roles in synthetic lethality according to previous studies. These results demonstrate the ability of our proposed method to predict synthetic lethal interactions and provide a basis for further characterization of these particular genetic combinations.
A computational analysis of synthetic lethality was performed in this study. Synthetic lethality gene pairs were encoded via enrichment theory of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Advanced computational methods were adopted to build an optimal prediction model and extract important features.
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